IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0248893.html
   My bibliography  Save this article

Placing sensors in sewer networks: A system to pinpoint new cases of coronavirus

Author

Listed:
  • Mehdi Nourinejad
  • Oded Berman
  • Richard C Larson

Abstract

We consider a proposed system that would place sensors in a number of wastewater manholes in a community in order to detect genetic remnants of SARS-Cov-2 found in the excreted stool of infected persons. These sensors would continually monitor the manhole’s wastewater, and whenever virus remnants are detected, transmit an alert signal. In a recent paper, we described two new algorithms, each sequentially opening and testing successive manholes for genetic remnants, each algorithm homing in on a neighborhood where the infected person or persons are located. This paper extends that work in six important ways: (1) we introduce the concept of in-manhole sensors, as these sensors will reduce the number of manholes requiring on-site testing; (2) we present a realistic tree network depicting the topology of the sewer pipeline network; (3) for simulations, we present a method to create random tree networks exhibiting key attributes of a given community; (4) using the simulations, we empirically demonstrate that the mean and median number of manholes to be opened in a search follows a well-known logarithmic function; (5) we develop procedures for determining the number of sensors to deploy; (6) we formulate the sensor location problem as an integer nonlinear optimization and develop heuristics to solve it. Our sensor-manhole system, to be implemented, would require at least three additional steps in R&D: (a) an accurate, inexpensive and fast SARS-Cov-2 genetic-remnants test that can be done at the manhole; (b) design, test and manufacture of the sensors; (c) in-the-field testing and fine tuning of an implemented system.

Suggested Citation

  • Mehdi Nourinejad & Oded Berman & Richard C Larson, 2021. "Placing sensors in sewer networks: A system to pinpoint new cases of coronavirus," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-25, April.
  • Handle: RePEc:plo:pone00:0248893
    DOI: 10.1371/journal.pone.0248893
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0248893
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0248893&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0248893?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Richard C Larson & Oded Berman & Mehdi Nourinejad, 2020. "Sampling manholes to home in on SARS-CoV-2 infections," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-20, October.
    2. Oded Berman & Richard C. Larson & Nikoletta Fouska, 1992. "Optimal Location of Discretionary Service Facilities," Transportation Science, INFORMS, vol. 26(3), pages 201-211, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chung, Sung Hoon & Kwon, Changhyun, 2015. "Multi-period planning for electric car charging station locations: A case of Korean Expressways," European Journal of Operational Research, Elsevier, vol. 242(2), pages 677-687.
    2. Bogyrbayeva, Aigerim & Kwon, Changhyun, 2021. "Pessimistic evasive flow capturing problems," European Journal of Operational Research, Elsevier, vol. 293(1), pages 133-148.
    3. Kuby, Michael & Lim, Seow, 2005. "The flow-refueling location problem for alternative-fuel vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 39(2), pages 125-145, June.
    4. Wang, Ying-Wei & Lin, Chuah-Chih, 2013. "Locating multiple types of recharging stations for battery-powered electric vehicle transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 58(C), pages 76-87.
    5. Averbakh, Igor & Berman, Oded, 1996. "Locating flow-capturing units on a network with multi-counting and diminishing returns to scale," European Journal of Operational Research, Elsevier, vol. 91(3), pages 495-506, June.
    6. Tommy Carpenter & Andrew Curtis & S. Keshav, 2014. "The return on investment for taxi companies transitioning to electric vehicles," Transportation, Springer, vol. 41(4), pages 785-818, July.
    7. Ventura, Jose A. & Kweon, Sang Jin & Hwang, Seong Wook & Tormay, Matthew & Li, Chenxi, 2017. "Energy policy considerations in the design of an alternative-fuel refueling infrastructure to reduce GHG emissions on a transportation network," Energy Policy, Elsevier, vol. 111(C), pages 427-439.
    8. S. A. MirHassani & R. Ebrazi, 2013. "A Flexible Reformulation of the Refueling Station Location Problem," Transportation Science, INFORMS, vol. 47(4), pages 617-628, November.
    9. Yıldız, Barış & Arslan, Okan & Karaşan, Oya Ekin, 2016. "A branch and price approach for routing and refueling station location model," European Journal of Operational Research, Elsevier, vol. 248(3), pages 815-826.
    10. Li, Xiaopeng & Ma, Jiaqi & Cui, Jianxun & Ghiasi, Amir & Zhou, Fang, 2016. "Design framework of large-scale one-way electric vehicle sharing systems: A continuum approximation model," Transportation Research Part B: Methodological, Elsevier, vol. 88(C), pages 21-45.
    11. Yıldız, Barış & Olcaytu, Evren & Şen, Ahmet, 2019. "The urban recharging infrastructure design problem with stochastic demands and capacitated charging stations," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 22-44.
    12. David Schindl & Nicolas Zufferey, 2015. "A learning tabu search for a truck allocation problem with linear and nonlinear cost components," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(1), pages 32-45, February.
    13. Gautam, N., 2002. "Performance analysis and optimization of web proxy servers and mirror sites," European Journal of Operational Research, Elsevier, vol. 142(2), pages 396-418, October.
    14. Shen, Zuo-Jun Max & Feng, Bo & Mao, Chao & Ran, Lun, 2019. "Optimization models for electric vehicle service operations: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 462-477.
    15. Lin, Zhenhong & Ogden, Joan & Fan, Yueyue & Chen, Chien-Wei, 2009. "The Fuel-Travel-Back Approach to Hydrogen Station Siting," Institute of Transportation Studies, Working Paper Series qt14p44238, Institute of Transportation Studies, UC Davis.
    16. Monir Sabbaghtorkan & Rajan Batta & Qing He, 2022. "On the analysis of an idealized model to manage gasoline supplies in a short-notice hurricane evacuation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(3), pages 911-945, September.
    17. Rabl, Regina & Reuter-Oppermann, Melanie & Jochem, Patrick E.P., 2024. "Charging infrastructure for electric vehicles in New Zealand," Transport Policy, Elsevier, vol. 148(C), pages 124-144.
    18. Capar, Ismail & Kuby, Michael & Leon, V. Jorge & Tsai, Yu-Jiun, 2013. "An arc cover–path-cover formulation and strategic analysis of alternative-fuel station locations," European Journal of Operational Research, Elsevier, vol. 227(1), pages 142-151.
    19. Rawan Shabbar & Anemone Kasasbeh & Mohamed M. Ahmed, 2021. "Charging Station Allocation for Electric Vehicle Network Using Stochastic Modeling and Grey Wolf Optimization," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    20. Gzara, Fatma & Erkut, Erhan, 2009. "A Lagrangian relaxation approach to large-scale flow interception problems," European Journal of Operational Research, Elsevier, vol. 198(2), pages 405-411, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0248893. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.